Velocity Filter Algorithms For Improved Target Detection And Tracking With Multiple-Scan Data

Kendall, William B.; Stocker, Alan D.; Jacobi, William J.

doi:10.1117/12.960347

Cited by 4 publications

(2 citation statements)

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“…The "track before detect" algorithm is a temporal based algorithm which uses multiple frames to incorporate temporal as well as spatial information. A lot of techniques and algorithms was developed within this concept of processing as 3-D matched filtering [8,9], Velocity filter banks [10,11], multistage IIR filter [12,13], Temporal Profile Based detection [14], Temporal filters [15,16], triple temporal filter (TTF) [17], bilateral TTF [18], dynamic programming [19,20], sequential detection [21], parallel spatial and temporal filtering [4,22] and Probabilistic data association (PDA) [23], etc.…”

Section: Introductionmentioning

confidence: 99%

New Approach in Processing of the Infrared Image Sequence for Moving Dim Point Targets Detection

Abdo¹,

Li²

2013

JSIP

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The development of an efficient moving target detection algorithm in IR-image sequence is considered one of the most critical research fields in modern IRST (Infrared Search and Track) systems, especially when dealing with moving dim point targets. In this paper we propose a new approach in processing of the Infrared image sequence for moving dim point targets detection built on the transformation of the IR-image sequence into 4-vectors for each frame in the sequence. The results of testing the proposed approach on a set of frames having a simple single pixel target performing a different motion patterns show the validity of the approach for detecting the motion, with simplicity in calculation and low time consumption.

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Section: Introductionmentioning

confidence: 99%

New Approach in Processing of the Infrared Image Sequence for Moving Dim Point Targets Detection

Abdo¹,

Li²

2013

JSIP

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“…Recently-developed signal processing algorithms utilizing multi-frame track-before-detect or velocity filtering techniques provide optimum or near-optimum detection as well as robust track initiation for both single and multiple targets [1][2][3][4] . Since these algorithms are computationally very intensive, however, their use has generally not been practical for realtime applications, especially in cases where there are stringent limitations on size, weight and power (as for example in tactical missile guidance or space-based surveillance).…”

Section: Introductionmentioning

confidence: 99%

<title>Miniaturized real-time processor for image sequence analysis</title>

1990

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Powerful new signal processing algorithms are now becoming available for such tasks as the detection and tracking of multiple targets via image se quence analysis. For typical real-time applications, these algorithms require throughputs on the order of hundreds to thousands of MFLOPS. In order to achieve such throughputs, it is necessary to employ parallel processing architectures, which normally require large size, weight and power consumption for their implementation. We have developed a high-performance, programmable MIMD processor called the SCC-lOO which is particularly well-suited for miniaturization using hybrid wafer-scale packaging technology. A 20-node configuration with a peak throughput in excess of 1 GFLOPS will be packaged in a three-inch cube using this approach.

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A sequential detection approach to target tracking

Blostein

Richardson²

1994

IEEE Trans. Aerosp. Electron. Syst.

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Velocity Filter Algorithms For Improved Target Detection And Tracking With Multiple-Scan Data

Cited by 4 publications

References 0 publications

New Approach in Processing of the Infrared Image Sequence for Moving Dim Point Targets Detection

New Approach in Processing of the Infrared Image Sequence for Moving Dim Point Targets Detection

<title>Miniaturized real-time processor for image sequence analysis</title>

A sequential detection approach to target tracking

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